• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.111-121
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• 2006

The classification using spectral angle is a new approach based on the fact that the spectra of the same type of surface objects in RS data are approximately linearly scaled variations of one another due to atmospheric and topographic effects. There are many researches on the unsupervised classification using spectral angle recently. Nevertheless, there are only a few which consider the characteristics of Hyperspectral data. On this study, we propose the ISOMUSAC(Iterative Self-Organizing Modified Unsupervised Spectral Angle Classification) which can supplement the defects of previous unsupervised spectral angle classification. ISOMUSAC uses the Angle Division for the selection of seed points and calculates the center of clusters using spectral angle. In addition, ISOMUSAC perform the iterative merging and splitting clusters. As a result, the proposed algorithm can reduce the time of processing and generate better classification result than previous unsupervised classification algorithms by visual and quantitative analysis. For the comparison with previous unsupervised spectral angle classification by quantitative analysis, we propose Validity Index using spectral angle.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.105-108
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• 1994

A comparative study was made of the valvular sounds produced by normal prosthetic valves with thrombosed prosthetic valves. Comparisons of the closing sound were made for the power frequency spectra associated with individual valves. We used periodogram approach to obtain the spectral characteristics of the valve. Spectral analysis system was tested in mock circulatory system by comparing normal valves with those produced by the same valves but having simulated thrombosis at the hinge of the valve. The heart sounds was recorded from two patients having normal mechanical valve and thrombosed mechanical valve. The estimated spectrum of the thrombosed mechanical valve displayed lower apparent peak frequency than that of the normal valve. The results showed that frequency spectra gave information pertinent to the valve malfunction. Sound spectral analysis is simple and alternative diagnostic tool for early detection of prosthetic valve mal function.

• Journal of Environmental Science International
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• v.15 no.4
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• pp.373-378
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• 2006

The western coast of South Korea is famous for its large and broad tidal lands. Nevertheless, land reclamation, which has been conducted on a large scale, such as Sihwa embankment construction project has accelerated coastal environmental changes in the embankment inland. For monitoring of environmental change, vegetation change detecting of the embankment inland were carried out and field survey data compared with Landsat TM, ETM+, IKONOS, and EOC satellite remotely sensed data. In order to utilize multi-temporal remotely sensed images effectively, all data set with pixel size were analyzed by same geometric correction method. To detect the tidal land vegetation change, the spectral characteristics and spatial resolution of Landsat TM and ETM+ images were analyzed by SMA(spectral mixture analysis). We obtained the 78.96% classification accuracy and Kappa index 0.2376 using March 2000 Landsat data. The SMA(spectral mixture analysis) results were considered with comparing of vegetation seasonal change detection method.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.83-91
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• 1997

A reactor vibration monitoring has been performed using neutron noise obtained from excore detectors for the safety operation, Traditionally, the spectral estimator based on Fourier analysis has been widely used in the noise analysis of the reactor system. If the bias is too severe, the resolution would not be adequate for a given application. One major motivation for the current interests in the parametric approach to spectral estimation is the apparent higher resolution achievable with these modern techniques. In considering an unbias, a consistency, an efficency, and a minimum lower bound of the statictic estimation, an AR model is appropriate for noise spectral estimation with sharp peaks but not deep valley. In order to select an appropriate model order, the lag value of autocorrleaton function is applied. Burg method to trace the vibration mode of RPV internal is the most sucuessful.

• Earthquakes and Structures
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• v.8 no.3
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• pp.681-697
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• 2015

Iran as one of the countries located on the Alpine-Himalayan seismic belt has recently experienced a few number of catastrophic earthquakes. A well-known index of how buildings are affected by earthquakes is through assessment of probable Peak Ground Acceleration (PGA) and structures' response spectra. In this research, active faults around Kerman and Birjand, two major cities in eastern parts of Iran, have been considered. Seismic catalogues are gathered to categorize effects of surrounding faults on seismicity of the region. These catalogues were further refined with respect to time and space based on Knopoff-Gardner algorithm in order to increase statistical independency of events. Probabilistic Seismic Hazard Analysis (PSHA) has been estimated for each of cities regarding 50, 100, 200 and 500 years of structures' effective life-span. These results subsequently have been compared with Deterministic Seismic Hazard Analysis (DSHA). It has been observed that DSHA not necessarily suggests upper bound of PSHA results. Furthermore, based on spectral Ground Motion Prediction Equations (GMPEs), Uniform Hazard Spectra (UHS) and spectral acceleration were provided for 2% and 10% levels of probability of exceedance. The results show that increasing source-to-site distance leads to spectral acceleration reduction regarding each fault. In addition, the spectral acceleration rate of variation would increase if the source-to-site distance decreases.

• Korean Journal of Remote Sensing
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• v.20 no.6
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• pp.369-382
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• 2004

The purpose of this study is the investigation of applicability of LSMA(Linear Spectral Mixture Analysis) on the geological uses with different radiometric and spatial types of sensor images such as Terra ASTER and LANDSAT 7 ETM+. As for the actual application case, geologic mapping for mineral exploration using ASTER and ETM+ at the Mongolian plateau region was carried out. After the pre-processing such as the geometric corrections and calibration of radiance, 7 endmembers, as spectral classes for geologic rock types, related to spectral signature deviation for the given application was determined by the pre-surveyed geological mapping information and the correlation matrix analysis, and total 20 images of ASTER and ETM+ were used to LSMA processing. As the results, fraction maps showing individual mineral types in the study area are presented. It concluded that this approach based on LSMA using ETM+ and ASTER is regarded as one of the effective schemes for geologic remote sensing.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.106-109
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• 2000

There have been proposed two types of low bit rate vocoder upto now : One is MBE type using the spectrum modeling and another is CELP type using the hybrid coding method. CELP type vocoder has mainly studied between them. Specially, much of intensity is concentrated in CELP vocoder due to the emergence of Internet Phone and PCS in a domestic. In order to improve the speech quality in CELP vocoder, in this paper, we proposed a new spectrum analysis algorithm with variable window, In CELP vocoder, the spectrum of the synthesised speech signal is distorted because the fixed size windows is used for spectrum analysis. So we have measured the spectral leakage and in order to minimize the spectral leakage have adjusted the window size. Applying this method G.723.1 ACELP, we can get SD(Spectral Distortion) reduction 0.084(dB), residual energy reduction 6.3% and MOS(Mean Opinion Score) improvement 0.1.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.587-599
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• 1995

This paper proposes a method for pattern recognition using spectral analysis and a hybrid genetic-neural-fuzzy networks. The feature vectors using spectral analysis on contour sequences of 2-D images are extracted, and the vectors are not effected by translation, rotation and scale variance. A combined model using the advantages of conventional method is proposed, those are supervised learning BP, global searching genetic algorithm, and unsupervised learning fuzzy c-method. The proposed method is applied to 10 aircraft recognition to confirm the performance of the method. The experimental results show that the proposed method is better accuracy than conventional method using BP or fuzzy c-method, and learning speed is enhanced.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.12
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• pp.63-73
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• 2013

The parameters of electromechanical modes offer considerable insight into the dynamic stability properties of a power system. This paper presents a results of a LFO(low-frequency oscillation) based on the time-synchronized signals measured by synchrophasor in the rolling blackout. Spectral analysis was performed, and critical parameters were estimated using the data acquired from synchrophasors installed in the KEPCO system. As significant modes, a 0.68 Hz oscillation mode that occurred prior to the forced load shedding in the rolling blackout was estimated. Such an oscillation mode can cause an uncontrollable blackout. Therefore, the system should be operated so that significant oscillation modes are not activated. This results can serve as a reference in the future for reliable system operation in the event of a similar blackout.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.8
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• pp.741-746
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• 2007

In this study, transfer path identification and output estimation are simulated by multi-dimension spectral analysis method (MDSA). Multi -input/single-output system give expression the vehicle suspension which each inputs are correlated reciprocally. In case of correlating with inputs, the system needs separating the each input signal by MDSA. Main simulations are about finding effective input by coherent output spectrum and selecting optimal input's number by multiple coherence function. Also, by shielding transfer path of each input, transfer path characteristic is identified in terms of overall integrated contribution level.